Simple Linear Feedback and Extremum Seeking Control of GDI Engines

A novel approach to the control of a GDI engine is presented.Conventional control of car engines is normally based on extensive use of engine maps, i.e., matrix-based lookup tables that have been derived through extensive engine test bench experiments. This is an open loop approach which can be sensitive to engine-to-engine variations and variations due to aging and wear. In this paper it is shown, using simulations based on a calibrated GDI engine model, that it is possible to instead employ simple feedback control strategies with a low number of tuning parameters and yet achieve good control performance, provided the effective torque is available as a signal.It is also shown that extremum control can be used to find optimal operating... (More)

A novel approach to the control of a GDI engine is presented.Conventional control of car engines is normally based on extensive use of engine maps, i.e., matrix-based lookup tables that have been derived through extensive engine test bench experiments. This is an open loop approach which can be sensitive to engine-to-engine variations and variations due to aging and wear. In this paper it is shown, using simulations based on a calibrated GDI engine model, that it is possible to instead employ simple feedback control strategies with a low number of tuning parameters and yet achieve good control performance, provided the effective torque is available as a signal.It is also shown that extremum control can be used to find optimal operating conditions of the engine. The controller consists of a combination of subcontrollers, where torque feedback is a central part. The subcontrollers are with a few exceptions designed using simple linear feedback and feedforward control design methods. A silent extremum controller is used to minimize the fuel consumption and emissions in stratified mode by finding an optimal air/fuel ratio end EGR flow. The controller has been evaluated on the European driving cycle using a dynamic simulation model, and compares well with traditional table based engine control, with respect to tracking performance, ride comfort and fuel consumption. The strategy has proven to be robust to engine variations and disturbances. The results show that it is possible to design engine management systems with little prior knowledge of engine model parameters if feedback control and online optimization are used extensively. The work presented in this paper has been performed within the EU/Esprit LongTerm Research project FAMIMO, with Siemens Automotive as industrial partner. (Less)

@misc{cb45bbb0-b84d-4c9c-997f-9d62198a80bf,
abstract = {A novel approach to the control of a GDI engine is presented.Conventional control of car engines is normally based on extensive use of engine maps, i.e., matrix-based lookup tables that have been derived through extensive engine test bench experiments. This is an open loop approach which can be sensitive to engine-to-engine variations and variations due to aging and wear. In this paper it is shown, using simulations based on a calibrated GDI engine model, that it is possible to instead employ simple feedback control strategies with a low number of tuning parameters and yet achieve good control performance, provided the effective torque is available as a signal.It is also shown that extremum control can be used to find optimal operating conditions of the engine. The controller consists of a combination of subcontrollers, where torque feedback is a central part. The subcontrollers are with a few exceptions designed using simple linear feedback and feedforward control design methods. A silent extremum controller is used to minimize the fuel consumption and emissions in stratified mode by finding an optimal air/fuel ratio end EGR flow. The controller has been evaluated on the European driving cycle using a dynamic simulation model, and compares well with traditional table based engine control, with respect to tracking performance, ride comfort and fuel consumption. The strategy has proven to be robust to engine variations and disturbances. The results show that it is possible to design engine management systems with little prior knowledge of engine model parameters if feedback control and online optimization are used extensively. The work presented in this paper has been performed within the EU/Esprit LongTerm Research project FAMIMO, with Siemens Automotive as industrial partner.},
author = {Gäfvert, Magnus and Årzén, Karl-Erik and Pedersen, Lars Malcolm},
isbn = {89-85000-00-4},
language = {eng},
publisher = {ARRAY(0xa32b738)},
series = {Seoul 2000 FISITA world automotive congress : proceedings},
title = {Simple Linear Feedback and Extremum Seeking Control of GDI Engines},
year = {2000},
}